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        <title>Anglicized Words and Misspelled Cognates in Native Language Identification</title>
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            <title>Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications</title>
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        <name type="personal">
            <namePart type="given">Helen</namePart>
            <namePart type="family">Yannakoudakis</namePart>
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        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
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    <abstract>In this paper, we present experiments that estimate the impact of specific lexical choices of people writing in a second language (L2). In particular, we look at misspelled words that indicate lexical uncertainty on the part of the author, and separate them into three categories: misspelled cognates, “L2-ed” (in our case, anglicized) words, and all other spelling errors. We test the assumption that such errors contain clues about the native language of an essay’s author through the task of native language identification. The results of the experiments show that the information brought by each of these categories is complementary. We also note that while the distribution of such features changes with the proficiency level of the writer, their contribution towards native language identification remains significant at all levels.</abstract>
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%0 Conference Proceedings
%T Anglicized Words and Misspelled Cognates in Native Language Identification
%A Markov, Ilia
%A Nastase, Vivi
%A Strapparava, Carlo
%Y Yannakoudakis, Helen
%Y Kochmar, Ekaterina
%Y Leacock, Claudia
%Y Madnani, Nitin
%Y Pilán, Ildikó
%Y Zesch, Torsten
%S Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F markov-etal-2019-anglicized
%X In this paper, we present experiments that estimate the impact of specific lexical choices of people writing in a second language (L2). In particular, we look at misspelled words that indicate lexical uncertainty on the part of the author, and separate them into three categories: misspelled cognates, “L2-ed” (in our case, anglicized) words, and all other spelling errors. We test the assumption that such errors contain clues about the native language of an essay’s author through the task of native language identification. The results of the experiments show that the information brought by each of these categories is complementary. We also note that while the distribution of such features changes with the proficiency level of the writer, their contribution towards native language identification remains significant at all levels.
%R 10.18653/v1/W19-4429
%U https://aclanthology.org/W19-4429
%U https://doi.org/10.18653/v1/W19-4429
%P 275-284

Markdown (Informal)

[Anglicized Words and Misspelled Cognates in Native Language Identification](https://aclanthology.org/W19-4429) (Markov et al., BEA 2019)

• Anglicized Words and Misspelled Cognates in Native Language Identification (Markov et al., BEA 2019)

ACL

• Ilia Markov, Vivi Nastase, and Carlo Strapparava. 2019. Anglicized Words and Misspelled Cognates in Native Language Identification. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 275–284, Florence, Italy. Association for Computational Linguistics.